Bayesian estimation and precision as the goal for data collection (expanded)

Precision as the goal for data collection, talk at U.C. Irvine, March 14, 2014.

Part 1: Rejecting null is not enough, also need estimate and precision. Bayesian estimation supersedes confidence intervals and "the new statistics".

Part 2: Two Bayesian ways to assess a null value. Highest density interval with region of practical equivalence. Bayesian model comparison and Bayes factor.

Part 3: Biased estimation in sequential testing and optional stopping.

Part 4: Monte Carlo study of biased estimation in sequential testing and optional stopping.

Parts 3 and 4 are elaborations of this previous blog post.